CN115657730B - Robust clustering formation control method for large-scale multi-rotor unmanned aerial vehicle - Google Patents
Robust clustering formation control method for large-scale multi-rotor unmanned aerial vehicle Download PDFInfo
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Abstract
The invention belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to a robust clustering formation control method for a large-scale multi-rotor unmanned aerial vehicle. Firstly, establishing a formation motion model of a multi-rotor unmanned aerial vehicle and a directed communication topological structure of a formation system; then, dividing the unmanned aerial vehicle formation network into a plurality of clusters by combining a graph theory; finally, a robust control law is designed, stable flight of the unmanned aerial vehicle formation under external wind disturbance is achieved, the problems that the traditional formation control method is limited by scale and large in calculation amount are effectively solved, and expected formation cooperative performance can be achieved.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to a robust clustering formation control method for a large-scale multi-rotor unmanned aerial vehicle.
Background
In recent years, with the rapid development of aerospace technologies, the formation technology of unmanned aerial vehicles is receiving more and more attention, and the unmanned aerial vehicle formation technology is widely applied to military and civil fields such as cooperative reconnaissance, precision agriculture, disaster management, environmental monitoring, aerial base stations and the like. Many rotor unmanned aerial vehicle can accomplish tasks such as VTOL, all-round navigation in narrow space as an important classification of unmanned aerial vehicle, simple structure, and have better mobility.
Unmanned aerial vehicle formation refers to certain formation arrangement and task allocation of a plurality of unmanned aerial vehicles according to a certain topological structure in order to meet task requirements. In actual tasks, the performance of the unmanned aerial vehicle formation system mainly depends on a formation controller, so that unmanned aerial vehicle formation control is one of key technologies for unmanned aerial vehicle system development and is an important technology for realizing the maintenance, adjustment and reconstruction of formation of multiple unmanned aerial vehicles.
In the prior art, some researches on a formation control method of multi-rotor unmanned aerial vehicles exist, a Chinese patent application with publication number CN113157000A discloses a flight formation cooperative obstacle avoidance self-adaptive control method based on a virtual structure and an artificial potential field, and a Chinese patent application with publication number CN110286694A discloses a multi-leader unmanned aerial vehicle formation cooperative control method. However, in the above patent application, the size of the drone cluster is relatively small, and the problem of external environment interference suffered by the drone is not considered. Along with the increase of the number of unmanned aerial vehicles, the computation amount of the control method is rapidly increased, so that the index of the cooperative difficulty is increased, and therefore the overall scale of the formation of the multi-rotor unmanned aerial vehicles in the method is limited.
Disclosure of Invention
Based on the defects of the prior art, the invention provides a robust clustering formation control method for a large-scale multi-rotor unmanned aerial vehicle, which comprises the steps of firstly establishing a multi-rotor unmanned aerial vehicle formation motion model and a directed communication topological structure of a formation system; then, dividing the unmanned aerial vehicle formation network into a plurality of clusters by combining a graph theory; finally, a robust control law is designed, stable flight of the unmanned aerial vehicle formation under external wind disturbance is achieved, and the problems that the traditional formation control method is limited by scale and large in calculation amount are effectively solved.
The complete technical scheme of the invention is as follows:
a robust clustering formation control method for large-scale multi-rotor unmanned aerial vehicles comprises the following steps:
step S1: and establishing a multi-rotor unmanned aerial vehicle formation motion model.
Unmanned planeiThe position and attitude motion model of (a) is:
wherein the content of the first and second substances,m i representing unmanned aerial vehiclesiThe mass of (a) of (b),c 3 represents a three-dimensional row vector, anc 3 =[0 0 1] T ，gWhich represents the constant of the attractive force,p i indicating unmanned aerial vehicleiIn the position during the flight of the aircraft,
indicating unmanned aerial vehicleiThe velocity vector in the inertial coordinate system is,v i representing unmanned aerial vehiclesiThe speed of the aircraft during the course of flight,
indicating unmanned aerial vehicleiThe acceleration during the course of a flight may be,R i representing an inertial coordinate system and a droneiA transformation matrix between the body coordinate systems,f i representing unmanned aerial vehiclesiThe input of the control force of (a),d v i, indicating unmanned aerial vehicleiDue to the external environment interference force caused by the influence of external natural wind,J i indicating unmanned aerial vehicleiThe moment of inertia of the rotor (c),
indicating unmanned aerial vehicleiAttitude angular velocity;
indicating unmanned aerial vehicleiThe attitude angular acceleration of (a);C i indicating unmanned aerial vehicleiThe matrix of model parameters of (2) is,M i indicating unmanned aerial vehicleiThe control torque of (a) is inputted,d m i, indicating unmanned aerial vehicleiThe external disturbance moment is influenced by external natural wind.
Step S2: and establishing a directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system.
NCommunication between each unmanned aerial vehicle is by directed graphG=(V, E, W) It is shown that,V={v 1 ,v 2 ,…v i , …v N means forNThe set of the individual nodes is then selected,
a set of edges is represented that are,W=[w ij ]representing a weight moment;
wherein the content of the first and second substances,w ij representing unmanned aerial vehiclesiAnd unmanned aerial vehiclejIf the communication state is unmanned planeiWith unmanned aerial vehiclejThere is information exchange between them, thenw ij =1, otherwisew ij =0, nodev i Is set by
Represent, define
Is a nodev i The degree of penetration of the (c) is,
is a nodev i To the out degree of (c), then the directed graphGIs a Laplace matrix ofL=D-W，D=diag{d i Regarding a root node of a multi-rotor unmanned aerial vehicle formation system as a formation center, and representing the root node as a formation centerp 0 =[x 0 y 0 z 0 ] 。
And step S3: based on the multi-rotor unmanned aerial vehicle formation motion model and the directed communication topological structure network, a clustering algorithm is designed, and the directed communication topological structure network is divided into a plurality of clusters.
Calculating the degree of entrance and the degree of exit of each node unmanned aerial vehicle according to the directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system established in the step S2, and if the degree of entrance of the unmanned aerial vehicle is smaller than the degree of exit, the unmanned aerial vehicle is regarded as a cluster head; if the in-degree of the unmanned aerial vehicle is not less than the out-degree, the unmanned aerial vehicle is regarded as a cluster member, whether a communication link exists between the cluster head unmanned aerial vehicle and the cluster member unmanned aerial vehicle or not is judged, and if the communication link exists, the cluster member unmanned aerial vehicle is called as a cluster member of the cluster head unmanned aerial vehicle and is added into the cluster.
And step S4: and (4) for the clusters divided in the step (S3), designing a position controller and an attitude controller for the cluster head and the cluster member respectively, and realizing safe and stable flight of multi-rotor unmanned aerial vehicle formation.
S401: cluster head unmanned aerial vehicleaPosition controller design
Wherein the content of the first and second substances,
unmanned plane capable of representing cluster headaIs input to the position control of the motor,K ap andK ad unmanned plane capable of indicating cluster headaThe gain matrix of the controller is then used,m a unmanned plane capable of indicating cluster headaThe mass of (a) of (b),sthe expression of the laplacian operator is used,k a unmanned plane capable of indicating cluster headaA constant parameter of the controller is set to be,p a unmanned plane capable of representing cluster headaIn the position during the flight of the aircraft,δ a unmanned plane capable of indicating cluster headaThe position deviation from the center of the formation,
unmanned plane capable of indicating cluster headaThe speed deviation from the center of the formation,
unmanned plane capable of indicating cluster headaThe velocity vector in the inertial coordinate system is,
unmanned plane capable of indicating cluster headaThe deviation of the acceleration from the center of the formation,
indicating cluster headsUnmanned planeaA position ambient interference estimator control input,b a unmanned plane capable of representing cluster headaAnd one-dimensional control parameters of the position channel external interference estimator.
S402, unmanned aerial vehicle of cluster memberbPosition controller design
Wherein the content of the first and second substances,
unmanned plane for representing cluster membersbIs input to the position control of the motor,
unmanned plane for representing cluster membersbThe location-external interference estimator controls the input,k b unmanned aerial vehicle for representing cluster membersbA positive controller constant parameter is set to be,m b unmanned plane for representing cluster membersbThe mass of (a) of (b),K bp andK bd unmanned plane for representing cluster membersbThe gain matrix of the position controller is,N b representing nodesv b The set of neighborhoods of (a),w bj unmanned plane for representing cluster membersbAnd unmanned aerial vehiclejThe state of communication of (a) is,p b unmanned plane for representing cluster membersbIn the position during the flight of the aircraft,p j indicating unmanned aerial vehiclejIn the position during the flight of the aircraft,δ bj unmanned aerial vehicle for representing cluster membersbWith unmanned aerial vehiclejThe positional deviation of (a) is small,
unmanned plane for representing cluster membersbThe velocity vector in the inertial coordinate system is,
representing unmanned aerial vehiclesjThe velocity vector in the inertial coordinate system is,
unmanned plane for representing cluster membersbThe speed deviation from the center of the formation,
unmanned plane for representing cluster membersbThe position deviation from the center of the formation,f b unmanned plane for representing cluster membersbAnd one-dimensional control parameters of the position channel external interference estimator.
S403. Unmanned planeiDesign of attitude controller
Wherein, the first and the second end of the pipe are connected with each other,
representing unmanned aerial vehiclesiThe attitude control input of (a) is performed,
indicating unmanned aerial vehicleiThe attitude disturbance estimator control input;K il andK ig representing unmanned aerial vehiclesiA gain matrix of the attitude controller is used,
indicating unmanned aerial vehicleiThe error of the posture is detected,
indicating unmanned aerial vehicleiThe error of the angular velocity of the attitude,
representing unmanned aerial vehiclesiThe desired attitude angle is set to a desired attitude angle,
indicating unmanned aerial vehicleiThe desired attitude angular velocity is the angular velocity of the vehicle,
indicating unmanned aerial vehicleiAn expected attitude angular acceleration;h i indicating unmanned aerial vehicleiOne-dimensional control parameters of the attitude channel external disturbance estimator,η i indicating unmanned aerial vehicleiAnd (4) attitude angle.
Compared with the prior art, the invention has the following advantages:
1. compared with the existing traditional unmanned aerial vehicle formation control method, the formation control method provided by the invention can effectively solve the problem of large-scale multi-rotor unmanned aerial vehicle formation, and better solves the problems of scale limitation and large calculation amount of the traditional method.
2. The formation control method can effectively inhibit the problem of external wind disturbance, has better robustness and can realize expected formation cooperative performance.
3. The robust clustering formation controller and the robust clustering formation method are simple in structure, low in algorithm complexity and easy to implement, can be used for formation control of aerospace vehicles, unmanned underwater vehicles or robots, and have universality.
Drawings
In order to illustrate embodiments of the present invention or technical solutions in the prior art more clearly, the drawings which are needed in the embodiments will be briefly described below, so that the features and advantages of the present invention can be understood more clearly by referring to the drawings, which are schematic and should not be construed as limiting the present invention in any way, and for a person skilled in the art, other drawings can be obtained on the basis of these drawings without any inventive effort.
Fig. 1 is a schematic diagram of two coordinate systems and attitude angle definitions for a multi-rotor drone.
Fig. 2 is a flow chart of a robust clustering formation control method for a large-scale multi-rotor unmanned aerial vehicle according to the invention.
Fig. 3 is a schematic diagram of the clustering of the multi-rotor drone formation system of the present invention.
Fig. 4 is a schematic structural diagram of a formation control system of a multi-rotor unmanned aerial vehicle according to the invention.
Fig. 5 is a three-dimensional trajectory curve of 26 multi-rotor unmanned aerial vehicles in flight according to an embodiment of the invention.
Fig. 6 is an attitude response curve of a 26-frame multi-rotor drone in an embodiment of the invention during flight.
Fig. 7 is a position error curve of a 26-frame multi-rotor drone in flight according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention, taken in conjunction with the accompanying drawings and detailed description, is set forth below. It should be noted that the embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Unmanned aerial vehicle formation system comprises a plurality of rotor unmanned aerial vehicle, and this system is when carrying out the task, and every unmanned aerial vehicle can be numbered according to certain order, and first unmanned aerial vehicle serial number is marked as 1, and the serial number of second unmanned aerial vehicle is marked as 2, and an arbitrary unmanned aerial vehicle serial number is marked as 1iAnd the last unmanned aerial vehicle number is recorded asN。
In the invention, in order to realize the state representation of the unmanned aerial vehicle, two coordinate systems are applied, one is an inertial coordinate systemE Ground -OXYZAnd the other is a body coordinate system of the unmanned planeE Body -OX b X b X b Respectively defined as:
(1) Inertial frame (E Ground -OXYZ): the inertial coordinate system is fixedly connected with the earth surface and the origin of the coordinate systemOIs selected to be on a point of the ground plane,OXthe axis points at random, the direction of the object is positive direction,OYaxis perpendicular toOXThe shaft is provided with a plurality of axial holes,OZthe axes are perpendicular to the other two axes and form a right-hand coordinate system.
(2) Body coordinate systemE Body -OX b X b X b : the body coordinate system is fixedly connected with the unmanned aerial vehicle body,O b at the center of mass of the drone (center of mass);O b X b the shaft is in the symmetrical plane of the unmanned aerial vehicle and is parallel to the design axis of the unmanned aerial vehicle and points to the front;O b Y b the shaft is perpendicular to the symmetry plane of the unmanned aerial vehicle and points to the right of the body;O b Z b the axis is in the plane of symmetry of the drone, withO b X b The axis is vertical and pointing upwards. Body coordinate systemE Body -OX b X b X b Forming a right-hand rectangular coordinate system.
As shown in fig. 1, any drone is in inertial frame(s) ((m))E Ground -OXYZ) The position of (1) is recorded as
p i =[x i y i z i ] T Wherein, in the step (A),x i indicating unmanned aerial vehicleiThe position in the X direction in the inertial coordinate system,y i indicating unmanned aerial vehicleiThe position in the Y direction in the inertial coordinate system,z i representing unmanned aerial vehiclesiPosition in the Z direction in the inertial frame.
Arbitrary unmanned planeiThe attitude angle in the body coordinate system is recorded asη i =[φ i θ i ψ i ] T Angle of rollφ i Angle of pitchθ i Yaw angleψ i Wherein, in the process,
roll angleφ i Indicating unmanned aerial vehicleiWound aroundO b X b The angle of rotation of the shaft.
Pitch angleθ i Representing unmanned aerial vehiclesiWound aroundO b Y b The angle of rotation of the shaft.
Yaw angleψ i Indicating unmanned aerial vehicleiWound aroundO b Z b The angle of rotation of the shaft.
As shown in fig. 2, in order to effectively solve the problems of scale limitation and large computation amount suffered by the conventional control method and ensure the stability and reliability of the large-scale multi-rotor unmanned aerial vehicle formation under external wind disturbance, the robust clustering formation control method for the large-scale multi-rotor unmanned aerial vehicle provided by the invention comprises the following steps:
step S1: building multi-rotor unmanned aerial vehicle formation motion model
Arbitrary unmanned planeiThe position and attitude motion model of (a) is:
wherein the content of the first and second substances,m i indicating unmanned aerial vehicleiThe mass of (a) is greater than (b),c 3 represents a three-dimensional row vector, anc 3 =[0 0 1] T ，gWhich represents the constant of the attractive force,p i indicating unmanned aerial vehicleiIn the position during the flight of the aircraft,
indicating unmanned aerial vehicleiThe velocity vector in the inertial coordinate system is,v i indicating unmanned aerial vehicleiThe speed of the aircraft during the course of flight,
indicating unmanned aerial vehicleiThe acceleration during the course of a flight may be,R i representing an inertial coordinate system and a droneiA transformation matrix between the body coordinate systems,d v i, indicating unmanned aerial vehicleiDue to the external environmental interference force caused by the influence of external natural wind,J i indicating unmanned aerial vehicleiIs rotatedThe inertia moment of the air conditioner is that,
indicating unmanned aerial vehicleiAn attitude angular velocity;
indicating unmanned aerial vehicleiThe attitude angular acceleration of (a);C i indicating unmanned aerial vehicleiThe matrix of model parameters of (2) is,M i representing unmanned aerial vehiclesiThe control torque of (a) is inputted,d m,i indicating unmanned aerial vehicleiDue to the external disturbance moment influenced by the external natural wind,f i indicating unmanned aerial vehicleiThe input of the control force of (a),
，
indicating unmanned aerial vehicleiAt a speed of 4 rotors in rotation,k if the coefficient of the moment is represented by,M i indicating unmanned aerial vehicleiControl moment input
，k iφ ，k iθ ，k iψ Representing the moment coefficient.
Step S2: directed communication topological structure network for establishing multi-rotor unmanned aerial vehicle formation system by combining graph theory method
NCommunication between each unmanned aerial vehicle is composed of directed graphsG=(V, E, W) It is shown that,V={v 1 ,v 2 ,…v i , …v N denotes thatNThe set of the individual nodes is then selected,
a set of edges is represented that are,W=[w ij ]representing a weight matrix;
wherein，w ij Indicating unmanned aerial vehicleiAnd unmanned aerial vehiclejIf the communication state is unmanned planeiWith unmanned aerial vehiclejThere is information exchange between them, thenw ij =1, otherwisew ij =0, nodev i Is set by
Represent, define
Is a nodev i The degree of penetration of the (c) is,
is a nodev i The degree of departure of (1) is then directed graphGIs the Laplace matrix ofL=D-W，D=diag{d i }。
If there is a node that makes the node have paths to all other nodes, the directed graphGA spanning tree is included and this node is called the root of the tree. Regarding a root node of the unmanned aerial vehicle formation system as a formation center, wherein the position of the root node in the three-dimensional space isp 0 =[x 0 y 0 z 0 ]。
And step S3: and designing a clustering algorithm to divide the directed communication topological structure network into a plurality of clusters.
According to the directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system established in the step S2, the entrance and exit degree information is obtained, and the entrance degree information of the unmanned aerial vehicle nodes is calculated
And time out information
. Comparing the out-degree value with the in-degree value ifd in (v i )-d out (v i )<0, then theThe drone is considered a cluster head. If the in-degree of the unmanned aerial vehicle is not less than the out-degree, the unmanned aerial vehicle is regarded as a cluster member, whether a communication link exists between the cluster head and the unmanned aerial vehicle of the cluster member is judged, and if the communication link exists between the cluster head and the unmanned aerial vehicle of the cluster memberAAnd (4) calling the cluster member unmanned aerial vehicle as a cluster member of the cluster head and joining the cluster through the communication link. Therefore, the directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system is divided into a plurality of clusters. As shown in fig. 3, the formation of 26 multi-rotor unmanned aerial vehicles is divided into 4 clusters, wherein the unmanned aerial vehicle with cluster head can receive the information from the formation center, and the rest unmanned aerial vehicles are corresponding cluster members respectively.
And step S4: robust position and attitude control laws are designed respectively for cluster heads and cluster members, and formation safe and stable flight is realized. The designed control law structure diagram is shown in fig. 4.
S401 Cluster head unmanned aerial vehicleaAnd the position controller is designed to obtain the control input of the cluster head position, so that the accurate control of the cluster head position is realized.
Wherein the content of the first and second substances,
unmanned plane capable of indicating cluster headaIs input by the position control of (a),K ap andK ad unmanned plane capable of indicating cluster headaThe gain matrix of the controller is then used,m a unmanned plane capable of representing cluster headaThe mass of (a) of (b),sthe expression of the laplacian operator is used,k a unmanned plane capable of indicating cluster headaA constant parameter of the controller is set to be,p a unmanned plane capable of indicating cluster headaIn the position during the flight of the aircraft,δ a unmanned plane capable of indicating cluster headaThe position deviation from the center of the formation,
unmanned plane capable of indicating cluster headaThe speed deviation from the center of the formation,
unmanned plane capable of indicating cluster headaThe velocity vector in the inertial coordinate system is,
unmanned plane capable of indicating cluster headaThe deviation of the acceleration from the center of the formation,
unmanned plane capable of indicating cluster headaA position ambient interference estimator control input,b a unmanned plane capable of representing cluster headaAnd one-dimensional control parameters of the position channel external interference estimator.
S402 cluster member unmanned aerial vehiclebAnd the position controller is designed to obtain the position control input of the cluster member, so that the accurate control of the cluster member is realized.
Wherein the content of the first and second substances,
unmanned plane for representing cluster membersbIs input by the position control of (a),
unmanned plane for representing cluster membersbThe location-external interference estimator controls the input,k b unmanned plane for representing cluster membersbA positive controller constant parameter is set to be,m b unmanned plane for representing cluster membersbThe mass of (a) of (b),K bp andK bd unmanned plane for representing cluster membersbThe gain matrix of the position controller is,N b representing nodesv b The neighborhood set of (a) is selected,w bj unmanned plane for representing cluster membersbAnd unmanned aerial vehiclejThe state of communication of (a) is,p b unmanned plane for representing cluster membersbDuring flightIn the position of (a) in the first,p j indicating unmanned aerial vehiclejIn the position during the flight of the aircraft,δ bj unmanned plane for representing cluster membersbWith unmanned aerial vehiclejThe positional deviation of (a) is small,
unmanned plane for representing cluster membersbThe velocity vector in the inertial coordinate system is,
indicating unmanned aerial vehiclejThe velocity vector in the inertial coordinate system is,
unmanned plane for representing cluster membersbThe speed deviation from the center of the formation,
unmanned plane for representing cluster membersbThe position deviation from the center of the formation,f b unmanned aerial vehicle for representing cluster membersbAnd one-dimensional control parameters of the position channel external interference estimator.
S403, designing attitude controllers of the cluster heads and the cluster members to obtain attitude control input, and realizing attitude stabilization.
Wherein the content of the first and second substances,
indicating unmanned aerial vehicleiThe attitude control input of (a) is performed,
representing unmanned aerial vehiclesiThe attitude disturbance estimator control input;K il andK ig indicating unmanned aerial vehicleiThe gain matrix of the attitude controller is,
indicating unmanned aerial vehicleiThe error of the posture is that the posture error,
indicating unmanned aerial vehicleiThe error of the angular velocity of the attitude,
indicating unmanned aerial vehicleiThe desired attitude angle is set to a desired attitude angle,
indicating unmanned aerial vehicleiThe desired attitude angular velocity is the angular velocity of the vehicle,
indicating unmanned aerial vehicleiAn expected attitude angular acceleration;h i indicating unmanned aerial vehicleiAnd (3) one-dimensional control parameters of the attitude channel external interference estimator.
In the invention, the input control instruction in the established formation motion model is as follows in consideration of the condition that unmanned aerial vehicle formation is subjected to various uncertain external interferences:
cluster head unmanned aerial vehicleaPosition control input of
Comprises the following steps:
wherein:c 3 =[0 0 1] T ，
unmanned plane capable of representing cluster headaThe input of the control force is controlled,
unmanned plane capable of indicating cluster headaInertial coordinate system and cluster head unmanned aerial vehicleaA transformation matrix between the body coordinate systems.
Cluster member unmanned aerial vehiclebPosition control input of
Comprises the following steps:
wherein, the first and the second end of the pipe are connected with each other,
unmanned aerial vehicle for representing cluster membersiThe input of the control force of (a),
unmanned plane for representing cluster membersbUnmanned aerial vehicle based on inertial coordinate system and cluster membersbA transformation matrix between the body coordinate systems.
Attitude control input for cluster head and cluster member drones
Comprises the following steps:
example 1
And (3) aiming at the constructed multi-rotor unmanned aerial vehicle formation system, under the external interference condition, establishing Matlab control system simulation. The invention performs emulation through a computer program running in a computer, a matlab (version number 2020 b) based platform. In a specific simulation scenario, it is considered that a formation of 26 multi-rotor drones performs a cooperative task. At the beginning, 26 multi-rotor unmanned aerial vehicles vertically take off from the ground and gradually form a hexagonal cubic formation in the air.
According to the step S1, the parameters of the unmanned aerial vehicle model are set as follows:m i =1kg, g=9.81m/s 2 , J i =[0.1090.1030.06] T kg·m^2。the external natural wind interference that many rotor unmanned aerial vehicle formation received does
The system initial conditions were set as follows:
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establishing a directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system as shown in fig. 3, and calculating the in-out value of each unmanned aerial vehicle according to the topological network established in the step S2. According to the clustering algorithm in the step S3, unmanned planes 1,7, 13 and 20 are selected as cluster heads, and the rest unmanned planes are selected as cluster members. The whole unmanned aerial vehicle cluster is divided into 4 unmanned aerial vehicle clusters.
Setting cluster head unmanned aerial vehicle position controller gain matrixK ap AndK ad is composed of
Setting parameters of external interference estimator of cluster head unmanned aerial vehicle position channelb a And =1. Unmanned aerial vehicle for setting cluster membersbGain matrix of position controllerK bp AndK bd is composed of
Setting parameters of external interference estimator of cluster head unmanned aerial vehicle position channelf a =1。
Attitude controller gain matrix for setting cluster head and cluster memberK il AndK ig is composed of
Setting attitude channel external interference estimator parameters of cluster head and cluster memberh i =20。
Calculating to obtain the control input of the unmanned aerial vehicle formation according to the parameter setting
，
，
Can realize that large-scale unmanned aerial vehicle formation is stably flown.
The simulation results are shown in fig. 5, 6 and 7, which are respectively a three-dimensional trajectory curve, an attitude response curve and a position error curve of 26 multi-rotor unmanned aerial vehicles when the unmanned aerial vehicles are flying in formation. As can be seen from fig. 5, the formation control method of the present invention enables the formation of multiple rotor drones to achieve synergy. In addition, the formation control method can effectively inhibit the influence of external interference. As can be seen from fig. 6 and 7, the tracking error is small, and the control accuracy requirement can be met.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. "beneath," "under" and "beneath" a first feature includes the first feature being directly beneath and obliquely beneath the second feature, or simply indicating that the first feature is at a lesser elevation than the second feature.
In the present invention, the terms "first", "second", "third" and "fourth" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The term "plurality" means two or more unless explicitly defined otherwise.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A robust clustering formation control method for large-scale multi-rotor unmanned aerial vehicles is characterized by comprising the following steps:
step S1: establishing a formation motion model of the multi-rotor unmanned aerial vehicle;
step S2: establishing a directed communication topological structure network of a multi-rotor unmanned aerial vehicle formation system;
and step S3: designing a clustering algorithm based on the multi-rotor unmanned aerial vehicle formation motion model and the directed communication topological structure network, and dividing the directed communication topological structure network into a plurality of clusters;
calculating the degree of entrance and the degree of exit of each node unmanned aerial vehicle according to the directed communication topological structure network of the multi-rotor unmanned aerial vehicle formation system established in the step S2, and if the degree of entrance of the unmanned aerial vehicle is smaller than the degree of exit, the unmanned aerial vehicle is regarded as a cluster head; if the in-degree of the unmanned aerial vehicle is not less than the out-degree, the unmanned aerial vehicle is regarded as a cluster member, whether a communication link exists between the cluster head unmanned aerial vehicle and the cluster member unmanned aerial vehicle or not is judged, if yes, the cluster member unmanned aerial vehicle is called as a cluster member of the cluster head unmanned aerial vehicle and is added into the cluster;
and step S4: for the clusters divided in the step S3, designing a position controller and an attitude controller respectively aiming at the cluster heads and cluster members to realize safe and stable flight of multi-rotor unmanned aerial vehicles formation;
the step S4 specifically includes:
s401: cluster head unmanned aerial vehicleaPosition controller design
Wherein the content of the first and second substances,
unmanned plane capable of indicating cluster head
Is input to the position control of the motor,
and
unmanned plane capable of indicating cluster head
The gain matrix of the controller takes the root node of the multi-rotor unmanned aerial vehicle formation system as a formation center and is expressed as
，
Which represents the constant of the attractive force,
represents a three-dimensional row vector, an
，
Unmanned plane capable of indicating cluster head
The mass of (a) of (b),
the expression of the laplacian operator is shown,
unmanned plane capable of representing cluster head
A constant parameter of the controller is set to be,
unmanned plane capable of representing cluster head
In the position during the flight of the aircraft,
unmanned plane capable of indicating cluster head
The position deviation from the center of the formation,
unmanned plane capable of indicating cluster head
The speed deviation from the center of the formation,
unmanned plane capable of indicating cluster head
The velocity vector in the inertial coordinate system is,
unmanned plane capable of indicating cluster head
The deviation of the acceleration from the center of the formation,
unmanned plane capable of representing cluster head
A position ambient interference estimator control input,
unmanned plane capable of indicating cluster head
One-dimensional control parameters of a position channel external interference estimator;
s402, unmanned aerial vehicle for cluster membersbPosition controller design
Wherein the content of the first and second substances,
unmanned plane for representing cluster members
Is input to the position control of the motor,
unmanned plane for representing cluster members
A position ambient interference estimator control input,
unmanned plane for representing cluster members
A positive controller constant parameter is set to be,
unmanned aerial vehicle for representing cluster members
The mass of (a) of (b),
and
unmanned plane for representing cluster members
The gain matrix of the position controller is,
representing nodes
The neighborhood set of (a) is selected,
unmanned plane for representing cluster members
And unmanned aerial vehicle
The state of communication of (a) is,
unmanned aerial vehicle for representing cluster members
In the position during the flight of the aircraft,
indicating unmanned aerial vehicle
In the position during the flight of the aircraft,
unmanned plane for representing cluster members
With unmanned aerial vehicle
The positional deviation of (a) is small,
unmanned plane for representing cluster members
The velocity vector in the inertial coordinate system is,
indicating unmanned aerial vehicle
The velocity vector in the inertial coordinate system is,
unmanned plane for representing cluster members
The speed deviation from the center of the formation,
unmanned plane for representing cluster members
The deviation from the position of the center of formation,
unmanned plane for representing cluster members
One-dimensional control parameters of a position channel external interference estimator;
s403. Unmanned planeiDesign of attitude controller
Wherein the content of the first and second substances,
representing unmanned aerial vehicles
The attitude control input of (a) is performed,
indicating unmanned aerial vehicle
The moment of inertia of the rotor (c),
indicating unmanned aerial vehicle
The matrix of model parameters of (2) is,
indicating unmanned aerial vehicle
The attitude disturbance estimator control input;
and
indicating unmanned aerial vehicle
A gain matrix of the attitude controller is used,
indicating unmanned aerial vehicle
The error of the posture is that the posture error,
representing unmanned aerial vehicles
The error of the angular velocity of the attitude,
indicating unmanned aerial vehicle
The desired attitude angle is set to a desired attitude angle,
indicating unmanned aerial vehicle
The desired attitude angular velocity is the angular velocity of the vehicle,
representing unmanned aerial vehicles
An expected attitude angular acceleration;
indicating unmanned aerial vehicle
One-dimensional control parameters of the attitude channel external disturbance estimator,
indicating unmanned aerial vehicle
And (6) attitude angle.
2. The robust clustering control method for large-scale multi-rotor unmanned aerial vehicles according to claim 1, wherein the unmanned aerial vehicles in step S1iThe position and posture motion model of (a) is:
wherein the content of the first and second substances,
indicating unmanned aerial vehicle
The mass of (a) is greater than (b),
indicating unmanned aerial vehicle
In the position during the flight of the aircraft,
indicating unmanned aerial vehicle
The velocity vector in the inertial coordinate system is,
indicating unmanned aerial vehicle
The speed of the aircraft during the course of flight,
indicating unmanned aerial vehicle
The acceleration during the flight of the aircraft,
representing an inertial coordinate system and an unmanned aerial vehicle
A transformation matrix between the body coordinate systems,
indicating unmanned aerial vehicle
The input of the control force of (a),
indicating unmanned aerial vehicle
Due to the external environmental interference force caused by the influence of external natural wind,
indicating unmanned aerial vehicle
Attitude angular velocity;
indicating unmanned aerial vehicle
The attitude angular acceleration of (a);
representing unmanned aerial vehicles
The control torque of (a) is inputted,
representing unmanned aerial vehicles
The external disturbance moment is influenced by external natural wind.
3. The robust clustering control method for large-scale multi-rotor unmanned aerial vehicles according to claim 1, wherein the step S2 specifically comprises:
wherein, the first and the second end of the pipe are connected with each other,
indicating unmanned aerial vehicle
And unmanned aerial vehicle
If the communication state is unmanned plane
With unmanned aerial vehicle
There is information exchange between them, then
Otherwise
Node of
Is set by
Express, define
Is a node
The degree of penetration of the (c) is,
is a node
The degree of departure of (1) is then directed graph
Is the Laplace matrix of
，
。
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